How NeRF Technology Is Creating the Next Generation of Media
The ways we create and consume visual media are constantly evolving, allowing us to experience places and things as if we’re physically present in those environments. Today, thanks to a fast-growing technology called a Neural Radiance Field ("NeRF"), anyone with a regular camera can make and share "3D photographs" of the real world. NeRFs have been around since the 2020 publication of Representing Scenes as Neural Radiance Fields for View Synthesis, but recent developments have made it easier than ever to start making immersive 3D media.
If you’ve ever viewed a 3D house tour or a 3D piece of furniture on an e-commerce website, you might be wondering: What makes NeRF unique? The answer is that NeRF introduces unprecedented photorealistic detail, including the ability to see reflections and transparencies like never before. You can see an example of NeRF in this capture created by our intern, Tyler McCormick:
NeRF makes high-quality 3D content creation fast and intuitive. CableLabs' Immersive Media Experiences team has been following the developments surrounding NeRF and other forms of immersive media to understand how these technologies transform the ways we live, learn, work and play. In time, immersive applications may emerge as major drivers of network traffic, so we’re working to understand the resources required to deliver these next-generation experiences.
In this blog post, we take a look at how NeRF works, how to use it yourself and how it’s influencing the future of immersive media.
NeRF in a Nutshell: How It Works
Essentially, NeRF is a machine learning system that takes photos or videos of a subject and memorizes the appearance of that subject in 3D. The NeRF-creation process looks something like this:
- Record a regular video or take a set of photos of your subject. Your phone will do!
- Take each of those images and figure out their positions relative to each other. You can do this with sensors fixed to the camera or, more easily, with an AI pipeline such as COLMAP.
- Train a multi-layer perceptron (a kind of neural network) to behave like a renderer that’s specialized at producing images of this subject.
- Now, you have a NeRF! You can use this neural network to create new images and videos of your subject, as in the above example.
When NeRF was first published in 2020, this creation process took hours. Today, advancements such as NVIDIA’s Instant Neural Graphics Primitives have brought the time down to the order of minutes or even seconds!
When we called NeRF a “3D photograph” earlier, we meant it. Essentially, a NeRF tries to describe the color and density of light emitted at each point in a 3D space. If you look at the same point of a real object from various angles, you might see different colors and densities. NeRF reproduces this effect to achieve reflections and transparencies, just as if you were viewing a real 3D object.
The NeRF process results in a high level of detail, but there’s one catch: The NeRF model assumes that you’re working with a still, unchanging scene. Light-based effects are “baked in,” meaning that you can’t add new objects to the scene and see them cast shadows or appear in reflections. If subjects move or change over time in the input video, the NeRF output will appear blurry or misshapen. New research papers have identified ways around these limitations, but those solutions haven’t yet reached wider adoption. In the meantime, anyone want to bring back the Mannequin Challenge?
It’s easy to start playing with NeRF. For example, Luma AI has built an app for iPhones and the web that automatically builds NeRFs from your videos. Once you have a NeRF, you can make videos and export them to other content-creation tools, including the Unreal game engine. Luma has a gallery of diverse NeRF-based content submitted by their users here.
If you want to take a more hands-on approach to NeRF creation, nerfstudio is a free, open-source toolset for creating NeRFs and designing advanced 3D graphics pipelines with the new technology. The learning curve is steeper, but power users and developers may enjoy the increased flexibility that this method offers.
NeRF and Next-Generation Media
Improved 3D capture of real-world subjects opens up opportunities across multiple industries. Here are a few examples.
Digital productions and VFX artists are already finding ways to incorporate NeRF into creative workflows. The most obvious use in content creation is converting real-world subjects to 3D representations that can be combined with synthetic content, but NeRF can also be used to smooth camera movements or compose multiple camera shots into unified sequences. To see for yourself, check out this Corridor Crew video on YouTube and this McDonald’s commercial about the Chinese New Year (including the additional behind-the-scenes content in the replies).
Digital twins and simulations, as described by platforms like NVIDIA Omniverse, have presented a compelling value proposition for accurate digital modeling of real-world systems such as factories and autonomous vehicles. Where applicable, NeRF may be an effective way to digitize real-world environments for use in models and simulations. One example in the wild is Wayve Technologies’ effort to build city-scale NeRFs for autonomous vehicle simulations, as presented at NVIDIA GTC 2023.
Finally, metaverse initiatives often aim to empower users to build and share their own content and experiences. Games like Minecraft and Roblox provide user-friendly content-creation tools, but photorealistic content creation is usually reserved for experts with training on professional tools or access to specialized photogrammetry software. Now, cloud-hosted apps like Luma and nerfstudio make it possible to generate photorealistic content in minutes with your smartphone and a network connection.
NeRF Is Accelerating Immersive Media
Immersive media comes in many forms, including but not limited to virtual reality, augmented reality, mixed reality and light field displays. NeRF alone isn’t going to make or break any of these technologies as they continue to mature and enter the market, but it gives creators and developers another tool to get one step closer to a photorealistic holographic immersive experience.
In the past, we’ve asked readers to imagine that we had a way to capture life-like holograms of subjects. Thanks to NeRF and related technologies, there's no need for make-believe. Subscribe to our blog for more updates from the Immersive Media Team and other activities at CableLabs.